Web frontend for reference extraction

This is a docker image that provides a web application to produce training material for ML-based reference extraction & segmentation engines. Currently supported are

• AnyStyle (Annotation & reference extraction)
• EXParser (Only editing of existing annotations; EXparser reference extraction was supported in v1.0.0)

The image provides a Web UI for producing training material which is needed to improve citation recognition for particular corpora of scholarly literature where the current models do not perform well.

A demo of the web frontend (without backend functionality) is available here.

Installation

1. Install Docker
2. Clone this repo with: git clone https://github.com/cboulanger/excite-docker.git && cd excite-docker
3. Build docker image: ./bin/build
4. If you want to use AnyCite, please consult its GitHub page on how to install it: https://github.com/inukshuk/anystyle

Use of the web frontend

1. Run server: ./bin/start-servers
2. Open frontend at http://127.0.0.1:8000/web/index.html
3. Click on "Help" for instructions (also lets you download the Zotero add-ons)

Zotero integration

You can connect the app to a local Zotero client to upload extracted references. This feature requires the installation of the following add-ons:

• Cita
• API-Endpoint

The webapp will then enable additional commands that let you retrieve the PDF attachment(s) of the currently selected item/collection, extract references from them and store them with the citing item.

If the Zotero storage folder is not located in ~/Zotero/storage, you need to rename .env.dist to .env and in this file, set the ZOTERO_STORAGE_PATH environment variable to the path pointing to this directory.